0.Description initial dataset
0.1 Data loading schema
0.2 Data description
Task 1: "Analyze vehicle speed"
1.1 Task pipeline schema
1.2 Pseudo-algorithm schema
1.2 Let's have a look on the data and summary stat.
Table: Data summary
| Name |
dt_hour |
| Number of rows |
1471 |
| Number of columns |
5 |
| Key |
NULL |
| _______________________ |
|
| Column type frequency: |
|
| character |
1 |
| factor |
1 |
| numeric |
3 |
| ________________________ |
|
| Group variables |
None |
Variable type: character
| type_vehicle |
0 |
1 |
1 |
1 |
0 |
3 |
0 |
Variable type: factor
| line_id |
0 |
1 |
FALSE |
73 |
6: 23, 3: 22, 5: 22, 7: 22 |
Variable type: numeric
| hour |
0 |
1 |
12.88 |
6.31 |
0.00 |
8.00 |
13.00 |
18.00 |
23.00 |
▃▇▆▇▇ |
| avg_speed_hour |
0 |
1 |
23.25 |
12.34 |
-0.01 |
13.91 |
22.74 |
31.25 |
60.27 |
▅▇▆▃▁ |
| avg_delay_hour |
0 |
1 |
347.65 |
181.75 |
-1.56 |
197.87 |
323.76 |
479.49 |
1740.08 |
▇▆▁▁▁ |
1.4 Visualize plots by moments and typology

Task 2: "Analyze vehicle delays in Seconds."
2.1 Task pipeline schema
2.2 Pseudo-algorithm schema
2.3 Visualization by moments and vehicle

2.4 Testing coordinates map w.r.t to stops
Data coordinates w.r.t to the stops
Plot test single coordinate